Dear Christine, The poisson family does not allow for overdispersion (nor underdispersion). Try using the quasipoisson family instead.
HTH, Thierry ------------------------------------------------------------------------ ---- ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, methodology and quality assurance Gaverstraat 4 9500 Geraardsbergen Belgium tel. + 32 54/436 185 thierry.onkel...@inbo.be www.inbo.be To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey -----Oorspronkelijk bericht----- Van: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] Namens Christine Griffiths Verzonden: maandag 18 mei 2009 13:26 Aan: r-help@r-project.org Onderwerp: [R] Overdispersion using repeated measures lmer Dear All I am trying to do a repeated measures analysis using lmer and have a number of issues. I have non-orthogonal, unbalanced data. Count data was obtained over 10 months for three treatments, which were arranged into 6 blocks. Treatment is not nested in Block but crossed, as I originally designed an orthogonal, balanced experiment but subsequently lost a treatment from 2 blocks. My fixed effects are treatment and Month, and my random effects are Block which was repeated sampled. My model is: Model<-lmer(Count~Treatment*Month+(Month|Block),data=dataset,family=pois son(link=sqrt)) Is this the only way in which I can specify my random effects? I.e. can I specify them as: (1|Block)+(1|Month)? When I run this model, I do not get any residuals in the error term or estimated scale parameters and so do not know how to check if I have overdispersion. Below is the output I obtained. Generalized linear mixed model fit by the Laplace approximation Formula: Count ~ Treatment * Month + (Month | Block) Data: dataset AIC BIC logLik deviance 310.9 338.5 -146.4 292.9 Random effects: Groups Name Variance Std.Dev. Corr Block (Intercept) 0.06882396 0.262343 Month 0.00011693 0.010813 1.000 Number of obs: 160, groups: Block, 6 Fixed effects: Estimate Std. Error z value Pr(>|z|) (Intercept) 1.624030 0.175827 9.237 < 2e-16 *** Treatment2.Radiata 0.150957 0.207435 0.728 0.466777 Treatment3.Aldabra -0.005458 0.207435 -0.026 0.979009 Month -0.079955 0.022903 -3.491 0.000481 *** Treatment2.Radiata:Month 0.048868 0.033340 1.466 0.142717 Treatment3.Aldabra:Month 0.077697 0.033340 2.330 0.019781 * --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Correlation of Fixed Effects: (Intr) Trt2.R Trt3.A Month T2.R:M Trtmnt2.Rdt -0.533 Trtmnt3.Ald -0.533 0.450 Month -0.572 0.585 0.585 Trtmnt2.R:M 0.474 -0.882 -0.402 -0.661 Trtmnt3.A:M 0.474 -0.402 -0.882 -0.661 0.454 Any advice on how to account for overdispersion would be much appreciated. Many thanks in advance Christine ---------------------- Christine Griffiths School of Biological Sciences University of Bristol Woodland Road Bristol BS8 1UG Tel: 0117 9287593 Fax 0117 925 7374 christine.griffi...@bristol.ac.uk http://www.bio.bris.ac.uk/research/mammal/tortoises.html ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer en binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is door een geldig ondertekend document. The views expressed in this message and any annex are purely those of the writer and may not be regarded as stating an official position of INBO, as long as the message is not confirmed by a duly signed document. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
